Tracking individual auditory attention during learning via EEG-based neural envelope tracking

Abstract

Attention is fundamental for classroom learning, yet measuring it during learning remains challenging. Behavioural measures are often subjective and lack the sensitivity to capture online momentary fluctuations in attention. This experiment examined the potential of EEG(Electroencephalography)-based neural envelope tracking (NET) as a measure of auditory attention to the teacher’s voice. Instead of measuring overall attention, NET considers where attention is directed to by correlating the teacher’s voice with the EEG-decoded stimulus. EEG data were collected while participants (n = 30) watched a video lecture on neuromyths that included attention manipulations (e.g., distraction, enhancement). Participants provided self-reports on attention levels during the lecture and completed a performance test on its content. Our results revealed that attention fluctuations induced by our manipulations were effectively captured by EEG-based NET measures, demonstrating the validity of NET as a valid measure of auditory attention during learning.

Simon Geirnaert

Postdoctoral researcher

My research interests include signal processing algorithm design for multi-channel biomedical sensor arrays (e.g., electroencephalography) with applications in attention decoding for brain-computer interfaces.